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DOI 10.1007/s00484-016-1197-9

Медицинская библиотека · International journal of biometeorology · 2016

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China.

Gou Faxiang, Liu Xinfeng, Ren Xiaowei, Liu Dongpeng, Liu Haixia, Wei Kongfu, Yang Xiaoting, Cheng Yao, Zheng Yunhe, Jiang Xiaojuan, Li Juansheng, Meng Lei, Hu Wenbiao

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Аннотация

The influence of socio-ecological factors on hand, foot and mouth disease (HFMD) were explored in this study using Bayesian spatial modeling and spatial patterns identified in dry regions of Gansu, China. Notified HFMD cases and socio-ecological data were obtained from the China Information System for Disease Control and Prevention, Gansu Yearbook and Gansu Meteorological Bureau. A Bayesian spatial conditional autoregressive model was used to quantify the effects of socio-ecological factors on the HFMD and explore spatial patterns, with the consideration of its socio-ecological effects. Our non-spatial model suggests temperature (relative risk (RR) 1.15, 95 % CI 1.01-1.31), GDP per capita (RR 1.19, 95 % CI 1.01-1.39) and population density (RR 1.98, 95 % CI 1.19-3.17) to have a significant effect on HFMD transmission. However, after controlling for spatial random effects, only temperature (RR 1.25, 95 % CI 1.04-1.53) showed significant association with HFMD. The spatial model demonstrates temperature to play a major role in the transmission of HFMD in dry regions. Estimated residual variation after taking into account the socio-ecological variables indicated that high incidences of HFMD were mainly clustered in the northwest of Gansu. And, spatial structure showed a unique distribution after taking account of socio-ecological effects.

Для цитирования: Gou Faxiang, Liu Xinfeng, Ren Xiaowei, Liu Dongpeng, Liu Haixia, Wei Kongfu, Yang Xiaoting, Cheng Yao, Zheng Yunhe, Jiang Xiaojuan, Li Juansheng, Meng Lei, Hu Wenbiao. Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China.. International journal of biometeorology. 2016. DOI: 10.1007/s00484-016-1197-9.

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